package cn.cihon.stream.wordcount

/**
  * Created by eeexiu on 16-11-20.
  */
/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

import org.apache.log4j.{Level, Logger}
import org.apache.spark.SparkConf
import org.apache.spark.storage.StorageLevel
import org.apache.spark.streaming.{Seconds, StreamingContext}

/**
  * Counts words in UTF8 encoded, '\n' delimited text received from the network every second.
  *
  * Usage: NetworkWordCount <hostname> <port>
  * <hostname> and <port> describe the TCP server that Spark Streaming would connect to receive data.
  *
  * To run this on your local machine, you need to first run a Netcat server
  *    `$ nc -lk 9999`
  * and then run the example
  *    `$ bin/run-example org.apache.spark.examples.streaming.NetworkWordCount localhost 9999`
  */
object NetworkWordCount {
  def main(args: Array[String]) {
//    if (args.length < 2) {
//      System.err.println("Usage: NetworkWordCount <hostname> <port>")
//      System.exit(1)
//    }

    // 屏蔽不必要的日志显示在终端上

    Logger.getLogger("org.apache.spark").setLevel(Level.WARN)

    Logger.getLogger("org.eclipse.jetty.server").setLevel(Level.OFF)

    // Create the context with a 1 second batch size
    val sparkConf = new SparkConf().setMaster("local[2]").setAppName("NetworkWordCount")
    val ssc = new StreamingContext(sparkConf, Seconds(1))

    // Create a socket stream on target ip:port and count the
    // words in input stream of \n delimited text (eg. generated by 'nc')
    // Note that no duplication in storage level only for running locally.
    // Replication necessary in distributed scenario for fault tolerance.
    val lines = ssc.socketTextStream("localhost", 9999, StorageLevel.MEMORY_AND_DISK_SER)
    val words = lines.flatMap(_.split(" "))
    val wordCounts = words.map(x => (x, 1)).reduceByKey(_ + _)
    wordCounts.print()
    ssc.start()
    ssc.awaitTermination()
  }
}
// scalastyle:on println

